Johanna Shi
In recent years, people pay more and more attention to the implementation of computer Vision projects, more and more models have been deployed in real business scenarios. However, when the business actually started to use, there would be a variety of requirements feedback on the model, and algorithm engineers began to need to continue iterative development and frequent deployment online. As the business evolves and models are applied in more and more scenarios, managing and maintaining so many model systems becomes a real challenge.
We agree with AlwaysAI's technology,below are four key guidelines to avoid common Computer Vision pitfalls:
Using alwaysAI's platform for training on the cloud, building, and deploying computer vision applications on the OpenNCC Edge AI Camera, would expedite the process of developing and deploying computer vision for production use cases such as health and safety monitoring, and more.
Watch the webinar to learn the Deployment Challenges with Computer Vision Applications.
Sergej Stoetzer
Dhiraj Gehlot
Alexander Sulaberidze
Anand Uthaman
The IBM Cloud AI camera is a powerful and flexible platform that allows you to train deep learning models in the cloud and run them on edge devices. It supports both convolutional neural networks (CNNs) and recurrent neural networks (RNNs). The IBM Cloud AI camera also has an onboard GPU for accelerated processing of large datasets. Getting free spins through https://gamblizard.ca/free-spins/ website is really good because there are a number of sites listed on it which are verified, authentic and highly profitable for new players.